{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true,
    "pycharm": {
     "name": "#%% colormaps, cmap, cm: 颜色表\n"
    }
   },
   "outputs": [],
   "source": [
    "# https://matplotlib.org/examples/color/colormaps_reference.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "data": {
      "text/plain": "array([[ 3, 15, 29],\n       [19,  5, 16],\n       [16, 11, 29]])"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = np.random.randint(1, 30, size=(3,3))\n",
    "data"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [
    {
     "data": {
      "text/plain": "['Solarize_Light2',\n '_classic_test_patch',\n 'bmh',\n 'classic',\n 'dark_background',\n 'fast',\n 'fivethirtyeight',\n 'ggplot',\n 'grayscale',\n 'seaborn',\n 'seaborn-bright',\n 'seaborn-colorblind',\n 'seaborn-dark',\n 'seaborn-dark-palette',\n 'seaborn-darkgrid',\n 'seaborn-deep',\n 'seaborn-muted',\n 'seaborn-notebook',\n 'seaborn-paper',\n 'seaborn-pastel',\n 'seaborn-poster',\n 'seaborn-talk',\n 'seaborn-ticks',\n 'seaborn-white',\n 'seaborn-whitegrid',\n 'tableau-colorblind10']"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看plt.style.use可选值\n",
    "plt.style.available"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [],
   "source": [
    "plt.style.use('seaborn-white')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x7fb7607c4e50>"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x7fb75e7cac10>"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(colormap=plt.cm.spring)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x7fb7629f7150>"
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(colormap='Set3')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x7fb762ff0a50>"
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 自定义的colormaps\n",
    "from matplotlib.colors import ListedColormap\n",
    "my_cm = ListedColormap(['orange', 'yellow', 'blue'])\n",
    "df.plot(colormap=my_cm)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  },
  "pycharm": {
   "stem_cell": {
    "cell_type": "raw",
    "source": [],
    "metadata": {
     "collapsed": false
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}